1. Field of the Invention
The present invention relates to a system for processing information.
2. Description of the Background Art
In the case of generating various reports using knowledge stored in the past, hitherto, it is necessary to retrieve a past report and refer to the content of the report by any method. In the case where a past report is constructed by using a template or the like, it is unnecessary to refer to the full text of the retrieved report. However, the relations among reports and the like have to be found out with reference to a huge amount of data.
For example, at the time of generating a so-called radiological report in a medical institution, when data is entered using a free format, usage of abbreviations, phrases, and the like largely vary among doctors in the department of radiology. It is therefore not easy to read radiological reports of other doctors. At the time of generating a radiological report of the same case, it is difficult to perform a work of generating a radiological report by referring to a radiological report of another doctor in the department of radiology.
Such a problem is not limited to the case of generating a radiological report but generally occurs in generation of various documents such as various reports and various scenarios.
To address the problem, a technique of extracting a value in accordance with a demand of a customer and supporting writing of an appealing scenario including a requirement and a solution is proposed (for example, Japanese Patent Application Laid-Open No. 2006-268405).
The technique proposed in Japanese Patent Application Laid-Open No. 2006-268405 is as follows. A value, a requirement, a solution, and the like are expressed as nodes, and the causal relations among them are preliminarily held as data (causal relation data). At the time of examining a proposal for a customer, nodes having the causal relation with a specific node are retrieved from the causal relation data, proper nodes are selected from the retrieved nodes, a requirement having the causal relation with a selected requirement is also retrieved as necessary, and a proper node is selected from the retrieved nodes. By repeating such operations, a scenario to be proposed is generated. Although the causal relation data is generated from known information in advance, it is also possible to define and add a new node and a new causal relation.
However, since the entire causal relation data is to be retrieved in the technique proposed in the patent document, a large amount of information related to a number of nodes other than a node to be selected is presented according to the situations. Consequently, the possibility that it takes time and effort to select or enter a node and an error occurs is high. For example, in the case where causal relation data is constructed by mixture of information of customers in quite different classes, there is high possibility that it takes time and effort to select or enter a node and an error occurs at the time of generating a scenario adapted to the class of actual customers.
Such a problem commonly occurs in the case of referring to information obtained by associating various elements with one another such as cases of generating various documents with reference to elements such as words.